| 基于Agent的报价学习对碳排放权拍卖的影响研究 |
| Research on the influence of bidding learning on the carbon emission right auction: Agent-based simulation |
| 摘要点击 1401 全文点击 0 投稿时间：2018-03-26 修订日期：2018-08-07 |
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| 中文关键词 碳排放权拍卖；报价学习行为；多Agent仿真；统一价格拍卖；歧视价格拍卖 |
| 英文关键词 Carbon emission auction; Bidding learning behavior; Multi-agent simulation; Uniform-price auction; Discriminatory-price auction |
| 基金项目 国家自然科学基金项目（面上项目，重点项目，重大项目）, |
| 作者 | 单位 | 邮编 | | 胡东滨 | 中南大学 | 410083 | | 胡紫娟 | 中南大学 | 410083 | | 陈晓红 | 湖南商学院 | |
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| 中文摘要 |
| 针对碳排放权序贯拍卖中竞标主体的报价学习行为对拍卖结果的影响, 引入自适应性报价模型并改进(particle swarm optimization)PSO智能算法来模拟控排企业报价动态变化的学习机制, 并构建基于多Agent的拍卖仿真模型, 实验分析不同拍卖情景下, 报价学习行为对碳排放权拍卖出清价格、年均履约水平以及拍卖效率的影响. 实验结果表明: 报价学习行为可以显著提高企业年均履约水平, 但是在歧视价格拍卖以及统一价格拍卖(市场供小于求时)下, 会显著降低碳排放权出清价格和拍卖效率; 歧视价格拍卖的出清价格和拍卖效率都高于统一价格拍卖, 但从公平性以及降低企业成本的角度出发, 统一价格拍卖可以减少拍卖对没有学习行为的竞标主体的不公平性以及避免报价学习行为对拍卖效率的影响. |
| 英文摘要 |
| For the impacts of bidder’ s learning bidding strategies on carbon allowance sequential auction,this paper introduced a self-adaptive pricing model and improved particle swarm optimization (PSO) algorithm to simulate the learning mechanism of the dynamic change of bidding prices. A multi-agent auction simulation model was constructed, to study the impacts of bidders’ learning behaviors on carbon allowance clearing prices, annual performance level, and auction efficiency under different experimental situations. The results show, the bidding learning behaviors significantly increase the average annual compliance level of the firms, and reduce the clearing price, auction efficiency under discriminatory-price auction and uniform-price auction (when market supply is less than demand). Meanwhile, discriminatory-price auctions have higher clearing prices and auction efficiency than uniform-price auctions. However, in view of fairness and reducing corporate
costs, uniform-price auctions reduce unfairness to firms who don’ t have bidding learning behaviors, and avoid the influence of bidding learning behaviors on auction efficiency. |
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